Currently, China is in the period of social transformation. Such transformation continuously results in high group polarization behaviors, which attracts many attentions. In order to explore the evolutionary mechanism and formation process of group polarization behavior, this paper proposes a group polarization model which is integrated into the Susceptible-Infected-Recovered-Susceptible (SIRS) epidemic model. In this paper, firstly, the SIRS epidemic model and the factors of relationship strength are introduced based on the J-A model (proposed by Jager and Amblard) to enhance the information transmission and interaction among individuals. In addition, the BA network (proposed by Barabasi and Albert) model is used as the agent adjacency model due to its closeness to the real social network structure. After that, the Monte Carlo method is applied to conduct experimental simulation. Subsequently, this paper analyzes the simulation results in threefold: (1) comparison of polarization processes with and without integration of the SIRS epidemic model; (2) adjusting the immune recovery parameter γ and the relationship strength z to explore the role of these two parameters in the polarization process; and (3) comparing the polarization effects of different network structures. Through the experiments, we find that BA network is more polarized than small-world network in the same scale. Finally, corresponding measures are proposed to prevent and mitigate the occurrence of group polarization.

Trichinellosis is a foodborne zoonotic disease caused by Trichinella spp., including Trichinella spiralis. In the present study, T. spiralis membrane-associated progesterone receptor component-2 (Ts-MAPRC2) gene was cloned and characterized using protein sequencing analysis. Furthermore, the expression, purification, immunoblot assay, binding ability with progesterone antibody, and immunofluorescence assay were performed. A direct effect of progesterone (P4) and mifepristone (RU486) on the Ts-MAPRC2 gene was determined using in vitro cell culture that showed different expression levels at all developmental stages (muscle larvae (ML), female adult worm (F-AL), male adult worm (M-AL), and newborn larvae (NBL)). Subsequently, the in vitro phenotypic effects of P4, RU486, and rTs-MAPRC2-Ab on F-AL and ML stages were measured. Later, the in vivo phenotypic effect and relative mRNA expression of mifepristone on the F-AL stage were studied. Our results revealed that the Ts-MAPRC2 gene is critical to maintaining pregnancy in the female adult worm (F-AL) of T. spiralis. The 300 ng/mL of P4 and 100 ng/mL of RU486 showed downregulation of the Ts-MAPRC2 gene in F-AL (p ≤ 0.05). This plays an important role in abortion and possibly decreases the worm burden of T. spiralis in the host. Only 30 ng/mL P4 showed significant upregulation in F-AL (p ≤ 0.05). The current study provides new insights regarding the antihormone (P4 and RU486) drug design and vaccine therapy of recombinant (rTs-MAPRC2) protein as well as their combined effects to control T. spiralis infection.

In recent years, social cluster events (mass events) take place frequently. The contradictions between social groups are gradually exposed, and their conflicts of interests and games are increasingly apparent. It comes with the fact that cluster behaviors are specifically manifested as cluster emergencies. According to statistics in the "Social Blue Book" in China over the past 10 years, mass incidents have occurred frequently. From 1993 to 2006, mass incidents were boosted from 8709 to 90,000, and even increased to more than 100,000 per year after 2010. When facing those events, people normally make decisions by their own opinions and the choices of surrounding people regarding their attitudes and behaviors. At the same time, with the influence of herd behavior, the individual decisions make these group events synchronized. For example, "candle-snatching

Summary With the advanced development of smart devices and network technique, Internet of Things has seen a large number of popular applications, among which, smart agriculture is a good example. The sensor nodes collect some parameters in the greenhouse, and send them to the control center. Then the control center can conduct some operations according to the analysis of the collected parameters. In this paper, we discuss how to efficiently aggregate and collect data with features of privacy protection in smart agricultural system. We propose an effective and scalable framework. The genetic algorithm is used to obtain the optimized data collection route for the agricultural system. The use of unmanned aerial vehicle also greatly improves the communication efficiency of resource‐constrained sensors in the system, which further increases the use time of the entire agricultural system. The experimental analysis shows that our framework has good efficiency and enjoys good scalability.

SummaryCurrently, group behaviors happen frequently with the development of network technology. As a typical social group behavior, group polarization has been attracted more and more academic attention due to its significant disturbance to public's daily lives. At present, the classic J‐A (proposed by Jager and Amblard) and D‐W (proposed by Deffuant and Weisbuch) models are used to analyze group polarization process. However, the main shortcomings existing in these models are that the individuals' psychology and their network relationships are rarely considered. In order to overcome the limitations, this article integrates the influence factors such as conformity and network relationship strength integrated into the polarization model. Besides, the BA (proposed by Barabasi and Albert) network model is used as the agent adjacency model due to its closer to the real social network structure. Subsequently, the experimental simulations are carried out with the multi‐agent Monte‐Carlo method so as to testify the efficiency and effectiveness. The results indicate that different information interaction modes have essential influence on group attitude polarization. Moreover, conformity parameters and the intensity of relationship have dual impacts on both speeding up and slowing down the polarization process.